• DocumentCode
    2364580
  • Title

    Study on automatic relaying algorithm for PLC based on channel state

  • Author

    Lu, Wenbing ; Luo, Yingli ; Bi, Xiaowei ; Ma, Yonghong ; Chen, Yongquan

  • Author_Institution
    Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    June 29 2010-July 1 2010
  • Firstpage
    81
  • Lastpage
    85
  • Abstract
    Relaying communication is a necessary means to improve the reliability of Meter Reading System (MRS) based on Power Line Carrier (PLC), but the searching for relaying path is one of the biggest challenges. According to the characteristics of PLC networks, an adaptive automatic relaying method based on the parameters of power line channel state and improved ant colony optimization algorithm is put forward in this paper. In the proposed algorithm, the restricted candidate list (RCL) strategy utilizing the greed stochastic adaptive searching method is also introduced according to the parameters of channel. The simulation and experimental results indicate that the algorithm can be adaptive to the channel state´s change by updating routing table dynamically, effectively improve the accuracy of relay and the success rate, and improve the search efficiency.
  • Keywords
    carrier transmission on power lines; optimisation; stochastic processes; telecommunication network reliability; PLC; ant colony optimization; automatic relaying algorithm; greed stochastic adaptive searching method; meter reading system; power line carrier; power line channel state; relaying communication; reliability; restricted candidate list; Electronic mail; Loading; PLC meter-reading system; amplitude parameter; ant colony optimization algorithm; automatic relaying algorithm; restricted candidate list (RCL);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems, Networks and Applications (ICCSNA), 2010 Second International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-7475-2
  • Type

    conf

  • DOI
    10.1109/ICCSNA.2010.5588771
  • Filename
    5588771